Speech recognition applications, such as call routing applications are used to execute commands in response to an input of natural speech utterance. Such applications invoke a speech recognition component that provides an output text or recognition for the input speech utterance. The output text is provided to a classifier which uses a classification model to output a class destination that is used by the application to execute the command in response to the input speech utterance.
For example for a call routing application, if the user utters “I want to talk to a customer representative” in response to an application prompt, the input utterance is recognized by the speech recognition component and the recognized text is provided to the classifier to route the call or inquiry to the customer service department based upon the classification model of the call routing application.
Classification models for speech or call routing applications are developed using domain-specific training data. The training data used in the development process includes speech utterances as well as manually transcribed text and class annotations (for the classification destinations) corresponding to each of the speech utterances. Manual transcription of the speech utterances is provided for example, by live agents that provide text recognition for each training utterance. Manually transcribing speech utterances for a large volume of speech training data is burdensome and increases development expense for call routing or other speech applications.
The discussion above is merely provided for general background information and is not intended to be used as an aid in determining the scope of the claimed subject matter.